Tool for Structural Testing of Rule-based System

Traditional software testing techinque are useful in testing some components of the expert systems, such as the interference engine. However, there is a need for the development of a testing method that tests the structure in a rule-based system. This testing method should be computationally effective, provide a reasonable level of coverage of the rule base, and be independent of the inference engine [KIPER92]. In the article Structural testing of Rule-based Expert Systems by Dr. JAmes D. Kiper, the logical path graph (LPG) method was chosen as a practical testing method for an expert system. However, the logical path graph algorithm developed in that paper requires further investigation by application to large rule bases. This need has resulted in the development of a computer tool called Graptool. The Graptool software, that has been created, was based on the logical path algorithm and was written in the C language. This tool reads the CLIPS rule-based expert system as a text file, and constructs a listing that represents the structure of the rule base

Methodology for testing and validating knowledge bases

A test and validation toolset developed for artificial intelligence programs is described. The basic premises of this method are: (1) knowledge bases have a strongly declarative character and represent mostly structural information about different domains, (2) the conditions for integrity, consistency, and correctness can be transformed into structural properties of knowledge bases, and (3) structural information and structural properties can be uniformly represented by graphs and checked by graph algorithms. The interactive test and validation environment have been implemented on a SUN workstation

Evolving Ensemble Fuzzy Classifier

The concept of ensemble learning offers a promising avenue in learning from data streams under complex environments because it addresses the bias and variance dilemma better than its single model counterpart and features a reconfigurable structure, which is well suited to the given context. While various extensions of ensemble learning for mining non-stationary data streams can be found in the literature, most of them are crafted under a static base classifier and revisits preceding samples in the sliding window for a retraining step. This feature causes computationally prohibitive complexity and is not flexible enough to cope with rapidly changing environments. Their complexities are often demanding because it involves a large collection of offline classifiers due to the absence of structural complexities reduction mechanisms and lack of an online feature selection mechanism. A novel evolving ensemble classifier, namely Parsimonious Ensemble pENsemble, is proposed in this paper. pENsemble differs from existing architectures in the fact that it is built upon an evolving classifier from data streams, termed Parsimonious Classifier pClass. pENsemble is equipped by an ensemble pruning mechanism, which estimates a localized generalization error of a base classifier. A dynamic online feature selection scenario is integrated into the pENsemble. This method allows for dynamic selection and deselection of input features on the fly. pENsemble adopts a dynamic ensemble structure to output a final classification decision where it features a novel drift detection scenario to grow the ensemble structure. The efficacy of the pENsemble has been numerically demonstrated through rigorous numerical studies with dynamic and evolving data streams where it delivers the most encouraging performance in attaining a tradeoff between accuracy and complexity.Comment: this paper has been published by IEEE Transactions on Fuzzy System

Knowledge-based support in Non-Destructive Testing for health monitoring of aircraft structures

Maintenance manuals include general methods and procedures for industrial maintenance and they contain information about principles of maintenance methods. Particularly, Non-Destructive Testing (NDT) methods are important for the detection of aeronautical defects and they can be used for various kinds of material and in different environments. Conventional non-destructive evaluation inspections are done at periodic maintenance checks. Usually, the list of tools used in a maintenance program is simply located in the introduction of manuals, without any precision as regards to their characteristics, except for a short description of the manufacturer and tasks in which they are employed. Improving the identification concepts of the maintenance tools is needed to manage the set of equipments and establish a system of equivalence: it is necessary to have a consistent maintenance conceptualization, flexible enough to fit all current equipment, but also all those likely to be added/used in the future. Our contribution is related to the formal specification of the system of functional equivalences that can facilitate the maintenance activities with means to determine whether a tool can be substituted for another by observing their key parameters in the identified characteristics. Reasoning mechanisms of conceptual graphs constitute the baseline elements to measure the fit or unfit between an equipment model and a maintenance activity model. Graph operations are used for processing answers to a query and this graph-based approach to the search method is in-line with the logical view of information retrieval. The methodology described supports knowledge formalization and capitalization of experienced NDT practitioners. As a result, it enables the selection of a NDT technique and outlines its capabilities with acceptable alternatives

The development of a program analysis environment for Ada

A unit level, Ada software module testing system, called Query Utility Environment for Software Testing of Ada (QUEST/Ada), is described. The project calls for the design and development of a prototype system. QUEST/Ada design began with a definition of the overall system structure and a description of component dependencies. The project team was divided into three groups to resolve the preliminary designs of the parser/scanner: the test data generator, and the test coverage analyzer. The Phase 1 report is a working document from which the system documentation will evolve. It provides history, a guide to report sections, a literature review, the definition of the system structure and high level interfaces, descriptions of the prototype scope, the three major components, and the plan for the remainder of the project. The appendices include specifications, statistics, two papers derived from the current research, a preliminary users' manual, and the proposal and work plan for Phase 2

Knowledge-based system V and V in the Space Station Freedom program

Knowledge Based Systems (KBS's) are expected to be heavily used in the Space Station Freedom Program (SSFP). Although SSFP Verification and Validation (V&V) requirements are based on the latest state-of-the-practice in software engineering technology, they may be insufficient for Knowledge Based Systems (KBS's); it is widely stated that there are differences in both approach and execution between KBS V&V and conventional software V&V. In order to better understand this issue, we have surveyed and/or interviewed developers from sixty expert system projects in order to understand the differences and difficulties in KBS V&V. We have used this survey results to analyze the SSFP V&V requirements for conventional software in order to determine which specific requirements are inappropriate for KBS V&V and why they are inappropriate. Further work will result in a set of recommendations that can be used either as guidelines for applying conventional software V&V requirements to KBS's or as modifications to extend the existing SSFP conventional software V&V requirements to include KBS requirements. The results of this work are significant to many projects, in addition to SSFP, which will involve KBS's